| pdata.frame {plm} | R Documentation |
An object of class 'pdata.frame' is a data.frame with an index attribute that describes its individual and time dimensions.
pdata.frame(x, index = NULL, drop.index = FALSE, row.names = TRUE,
stringsAsFactors = default.stringsAsFactors())
## S3 method for class 'pdata.frame'
x[i, j, drop]
## S3 method for class 'pdata.frame'
x[[y]]
## S3 method for class 'pdata.frame'
x$y
## S3 method for class 'pdata.frame'
print(x, ...)
## S3 method for class 'pdata.frame'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)
## S3 method for class 'pdata.frame'
as.list(x, keep.attributes = FALSE, ...)
x |
a |
i |
see |
j |
see |
y |
one of the columns of the |
index |
this argument indicates the individual and time indexes. See Details, |
drop |
see |
drop.index |
logical, indicates whether the indexes are to be excluded from the resulting pdata.frame, |
optional |
see |
row.names |
|
stringsAsFactors |
logical, indicating whether character vectors are to be converted to factors, |
keep.attributes |
logical, only for as.list, indicating the elements of the returned list should have the pdata.frame's attributes added (default: FALSE), |
... |
further arguments |
The index argument indicates the dimensions of the panel. It can be:
a vector of two character strings which contains the names of the individual and of the time indexes,
a character string which is the name of the individual index variable. In this case, the time index is created automatically and a new variable called “time” is added, assuming consecutive and ascending time periods in the order of the original data,
an integer, the number of individuals. In this case, the data need to be a balanced panel and be organized as a stacked time series (successive blocks of individuals, each block being a time series for the respective individual) assuming consecutive and ascending time periods in the order of the original data. Two new variables are added: “time” and “id” which contain the individual and the time indexes.
The "[[" and "$" extract
a series from the pdata.frame. The "index" attribute is
then added to the series and a class attribute "pseries" is
added. The "[" method behaves as for data.frame, except
that the extraction is also applied to the index attribute.
as.data.frame removes the index from the pdata.frame and
adds it to each column.
as.list behaves by default identical to as.list.data.frame
which means it drops the attributes specific to a pdata.frame; if a list of pseries
is wanted, the attribute keep.attributes can to be set to TRUE. This also
makes lapply work as expected on a pdata.frame (see also Examples).
a pdata.frame object: this is a data.frame with an
index attribute which is a data.frame with two
variables, the individual and the time indexes, both being factors.
The resulting pdata.frame is sorted by the individual index, then
by the time index. Any constant columns and all-NA columns are dropped.
Yves Croissant
pdim to check the dimensions of a 'pdata.frame' (and other objects),
pvar to check for each variable if it varies cross-sectionally and over time.
To check if the time periods are consecutive per individual, see is.pconsecutive.
# Gasoline contains two variables which are individual and time indexes
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop = TRUE)
# Hedonic is an unbalanced panel, townid is the individual index
data("Hedonic", package = "plm")
Hed <- pdata.frame(Hedonic, index = "townid", row.names = FALSE)
# In case of balanced panel, it is sufficient to give number of individuals
# data set 'Wages' is organized as a stacked time series
data("Wages", package = "plm")
Wag <- pdata.frame(Wages, 595)
# lapply on a pdata.frame by making it a list of pseries first
lapply(as.list(Wag[ , c("ed", "lwage")], keep.attributes = TRUE), lag)